Simulation grid for Carlotti and Parast (2026)

A dataset containing the grid of simulation results for Carlotti and Parast (2026) across two covariate settings: a binary covariate setting (setting 1) and a Gaussian covariate setting (setting 2). Each setting is run for 500 simulations, for a total of 1000 rows.

Usage

Carlotti_and_Parast_2026_simulations_grid

Format

A data frame with 1000 rows and 17 columns:

setting

The index of the simulation setting: 1 for the binary covariate setting (X_binary) and 2 for the Gaussian covariate setting (X_Gaussian).

simulation

The index of the simulation run.

n_sample

The sample size used.

n_chains

The number of MCMC chains used.

n_iterations

The number of MCMC iterations.

n_simulations

The total number of simulations per setting.

timestamp

The timestamp of execution.

seed

The random seed used.

BF_alternative

The alternative hypothesis used for the Bayes factor.

Bayesian_epsilon

The threshold for the Bayesian test.

frequentist_epsilon

The threshold for the frequentist test.

Bayesian_CI_upper

The upper bound of the Bayesian credible interval.

frequentist_CI_upper

The upper bound of the frequentist confidence interval.

Bayesian_coverage

Logical. Indicates if the true value is in the credible interval.

frequentist_coverage

Logical. Indicates if the true value is in the confidence interval.

Bayesian_power

Logical. Indicates if the Bayesian test rejected the null.

frequentist_power

Logical. Indicates if the frequentist test rejected the null.

Source

Generated using the code in the simulations folder of the BSET GitHub repository (https://github.com/PietroCarlotti/BSET).